| kernDeepStackNet-package | Kernel deep stacking networks with random Fourier transformation |
| calcTrA | Calculates the trace of the hat matrix |
| calcTrAFast | Calculates the trace of the hat matrix as C version |
| calcWdiag | Calculation of weight matrix |
| crossprodRcpp | Calculates the cross product of a matrix |
| devStandard | Predictive deviance of a linear model |
| EImod | Expected improvement criterion replacement function |
| fineTuneCvKDSN | Fine tuning of random weights of a given KDSN model |
| fineTuneKDSN | Fine tuning of random weights of a given KDSN model |
| fitKDSN | Fit kernel deep stacking network with random Fourier transformations |
| fourierTransPredict | Prediction based on random Fourier transformation |
| gDerivMu | Derivative of the link function evaluated at the expected values |
| getEigenValuesRcpp | Calculates the eigenvalues of a matrix |
| kernDeepStackNet | Kernel deep stacking networks with random Fourier transformation |
| lossCvKDSN | Kernel deep stacking network loss function based on cross-validation |
| lossGCV | Generalized cross-validation loss |
| lossKDSN | Kernel deep stacking network loss function |
| lossKDSNgivenModel | Kernel deep stacking network loss function based on model fit |
| mbo1d | Efficient global optimization in combination with one dimensional search |
| mboAll | Efficient global optimization inclusive meta model validation |
| optimize1dMulti | One dimensional optimization of multivariate loss functions |
| predict.KDSN | Predict kernel deep stacking networks |
| predLogProb | Predictive logarithmic probability of Kriging model |
| randomFourierTrans | Random Fourier transformation |
| robustStandard | Robust standardization |
| tuneKDSN | Tune kernel deep stacking network by direct optimization |
| tuneLevelGridKDSN | Tune kernel deep stacking network by direct optimization over a set of levels |
| tuneLevelKDSN | Tune kernel deep stacking network by direct optimization given level |
| tuneMboCvKDSN | Tuning of KDSN with efficient global optimization and cross-validation |
| tuneMboKDSN | Tuning of KDSN with efficient global optimization |
| tuneMboLevelCvKDSN | Tuning of KDSN with efficient global optimization given level by cross-validation |
| tuneMboLevelGridKDSN | Tuning of KDSN with efficient global optimization over a set of levels |
| tuneMboLevelKDSN | Tuning of KDSN with efficient global optimization given level |
| varMu | Variance function evaluated at expected value |